APPLICATION INSTRUCTIONS:

• CURRENT PENN STATE EMPLOYEE (faculty, staff, technical service, or student), please login to Workday to complete the internal application process. Please do not apply here, apply internally through Workday.

• CURRENT PENN STATE STUDENT (not employed previously at the university) and seeking employment with Penn State, please login to Workday to complete the student application process. Please do not apply here, apply internally through Workday.

• If you are NOT a current employee or student, please click “Apply” and complete the application process for external applicants.

 

Approval of remote and hybrid work is not guaranteed regardless of work location. For additional information on remote work at Penn State, see Notice to Out of State Applicants.

This is a term position; length of the term will be discussed during the interview process. Continuation past the term length discussed will be based on university need, performance, and/or availability of funding.

 

POSITION SPECIFICS

A postdoctoral position funded by the NIH is available immediately in the Laboratory of Dr. Santhosh Girirajan in the Departments of Biochemistry and Molecular Biology at The Pennsylvania State University focused on the integrative computational analysis of mouse models for autism-associated genes. The goal of this research program is to develop and apply advanced computational and machine learning approaches to understand how genetic variation shapes neurodevelopmental phenotypes across molecular, cellular, circuit, and behavioral levels.

The postdoctoral scholar will lead efforts to develop and implement machine learning and statistical frameworks for the integrative analysis of quantitative behavioral data, brain imaging datasets, single-cell RNA-sequencing, and spatial transcriptomics generated from large-scale mouse model studies. The position offers the opportunity to work in a highly collaborative, interdisciplinary environment at the interface of bioinformatics, computer science, neuroscience, and human genetics, with close interaction among experimental and computational teams.

Education and Experience

Applicants should hold a PhD in bioinformatics, computer science, computational biology, neuroscience, statistics, engineering, or a related field. Required qualifications include strong expertise in computational data analysis and statistics, with a high level of motivation to work with high-dimensional biological datasets. Demonstrated interest in or experience with machine learning methods is essential. Familiarity with one or more of the following areas is desirable: omics data analysis (e.g., single-cell RNA-seq, spatial transcriptomics), neuroimaging analysis, or quantitative behavioral data. Proficiency in Python, R, or related programming languages is required.

Applicants should also be willing to work with other investigators and mentor undergraduate and graduate students, as the research project emphasizes collaborative, team-based science.

Application Materials

Interested applicants should submit a cover letter describing research interests and relevant experienc